Data preprocessing

Merge the provided CSVs into one data-frame.

Checking training dataset attributes datatypes

after contact the datat sheets few observations and shape of the data-frame.

Build a popularity based model and recommend top 5 mobile phones

Build a collaborative filtering model using SVD

Collaborative filtering using KNN

KNN - User based model

Report your findings and inferences. Samsung Galaxy Note5 is the most popular product Amazon Customer is the most active author who writes reviews. Lenovo Vibe K4 Note (White,16GB) was rated by most of the authors CV rmse was 2.6

1)In what business scenario you should use CF based Recommendation Systems ?

Ans...)

Collaborative Filtering is used to building intelligent recommender systems that can learn to give better recommendations as more information about users is collected. It isa personalised recommender system , recommendations are made based on the past behaviour of the user. Most websites like Amazon, YouTube, and Netflix use collaborative filtering as a part of their sophisticated recommendation system.

2)In what business scenario you should use popularity based Recommendation Systems ?

Ans... )

Popularity based recommendation system relies on the popularity,trends and frequency counts of which items were most purchased.It is used buy the travel companies selling holiday packages in a season, by Google News and other news websites to show Top Stories with images.

3)What other possible methods can you think of which can further improve the recommendation for different users ?

Ans...)

Apart from Popularity and Collaborative Filtering , Content-based, Demographic, Utility based, Knowledge based and Hybrid recommendation system can be used as per the user needs.

summary

This works best if a business to start with initally. This recommendation system will help the users get a good recommendation to start with and once the buyers have a purchased history, the recommendation engine can use the model based collaborative filtering technique.